FACS技术在酶定向进化中的应用

doi:10.13560/j.cnki.biotech.bull.1985.2023-0486

摘要/Abstract

摘要：

流式细胞术（flow cytometry，FCM）是一种在单细胞水平上对大量细胞进行快速、相对定量的多参数分析技术。基于FCM建立的荧光激活细胞分选术（fluorescence-activated cell sorting，FACS）可物理分离荧光标记的单细胞，目前已被广泛应用于酶定向进化领域。定向进化已被证明是获得高酶活、强热稳定性、耐溶剂性等优良性质工业酶的有效方法，其首先需通过随机突变和DNA重组等方法构建酶突变文库，随后需在人工选择压力下对突变文库进行筛选。传统筛选方法如平板法、微孔板法等，存在通量低、成本高、误差大、准确性差等局限，无法实现对大型文库的高通量筛选。相较于传统筛选方法，FACS具有高通量、耗费低、误差小、精度高等优势。本文首先总结了FCM及FACS的发展进程，以及由此衍生的相关仪器的组成和分类，随后讨论了FACS在酶定向进化中的应用现状及现阶段的应用局限性，最后总结并展望了FACS发展方向及其在酶定向进化领域的应用前景。

关键词: 流式细胞术, 荧光激活细胞分选, 高通量筛选

Abstract:

Flow cytometry（FCM）is a rapid and relatively quantitative multi-parameter analytical technique for analyzing a large number of cells at the single-cell level. The constructed fluorescence activated cell sorting（FACS）based on FCM can physically separate fluorescent-labeled single cells and has been widely used in the field of directed evolution of enzyme. Directed evolution has been proven to be an effective method for obtaining industrial enzymes with excellent properties, such as high enzyme activity, strong thermal stability and solvent resistance. To conduct directed evolution, mutant library firstly needs to be constructed by random mutagenesis or DNA recombination, and then be screened under manual selection pressure. Traditional screening methods such as plate and microplate methods have limitations of low throughput, high cost, large errors, and poor accuracy, and cannot achieve high-throughput screening of large mutant library. Compared with traditional screening methods, FACS has the advantages of high throughput, low cost, small error and high precision. In this article, we first summarized the development process of FCM and FACS, as well as the composition and classification of related instruments derived from them. Then, we discussed the application status and limitations of FACS in the directed evolution of enzyme. Finally, we summarized and prospected the development direction of FACS and its application in the field of directed evolution of enzyme.

Key words: flow cytometry, fluorescence-activated cell sorting, high-throughput screening

刘金升, 陈振娅, 霍毅欣, 郭淑元. FACS技术在酶定向进化中的应用[J]. 生物技术通报, 2023, 39(10): 93-106.

LIU Jin-sheng, CHEN Zhen-ya, HUO Yi-xin, GUO Shu-yuan. Application of FACS Technology in the Directed Evolution of Enzyme[J]. Biotechnology Bulletin, 2023, 39(10): 93-106.

图/表 8

参考文献 94

[1]	Ur Rahman A, Khan S, Khan M. Transport of trans-activator of transcription(TAT)peptide in tumour tissue model: evaluation of factors affecting the transport of TAT evidenced by flow cytometry[J]. Journal of Pharmacy and Pharmacology, 2020, 72(4): 519-530. doi: 10.1111/jphp.13221 pmid: 31868235
[2]	Suo YZ, Gu ZQ, Wei XB. Advances of in vivo flow cytometry on cancer studies[J]. Cytometry A, 2020, 97(1): 15-23. doi: 10.1002/cyto.a.v97.1 URL
[3]	Burnie J, Tang VA, Welsh JA, et al. Flow virometry quantification of host proteins on the surface of HIV-1 pseudovirus particles[J]. Viruses, 2020, 12(11): 1296. doi: 10.3390/v12111296 URL
[4]	El-Hajjar L, Ali Ahmad F, Nasr R. A guide to flow cytometry: components, basic principles, experimental design, and cancer research applications[J]. Curr Protoc, 2023, 3(3): e721. doi: 10.1002/cpz1.v3.3 URL
[5]	Domínguez LM, Fiore EJ, Mazzolini GD. Generation and characterization of human mesenchymal stem/stromal cells for cell therapy applications[J]. Methods Cell Biol, 2022, 170: 189-202.
[6]	Midani FS, David LA. Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity[J]. Front Microbiol, 2023, 13: 910390. doi: 10.3389/fmicb.2022.910390 URL
[7]	Malone MK, Ujas TA, Cotter KM, et al. FACS to identify immune subsets in mouse brain and spleen[M]//Methods in Molecular Biology. New York, NY: Springer US, 2023: 213-229.
[8]	Becker S, Schmoldt HU, Adams TM, et al. Ultra-high-throughput screening based on cell-surface display and fluorescence-activated cell sorting for the identification of novel biocatalysts[J]. Curr Opin Biotechnol, 2004, 15(4): 323-329. doi: 10.1016/j.copbio.2004.06.001 URL
[9]	Zeymer C, Hilvert D. Directed evolution of protein catalysts[J]. Annu Rev Biochem, 2018, 87: 131-157. doi: 10.1146/annurev-biochem-062917-012034 pmid: 29494241
[10]	Sellés Vidal L, Isalan M, Heap JT, et al. A primer to directed evolution: current methodologies and future directions[J]. RSC Chem Biol, 2023, 4(4): 271-291. doi: 10.1039/D2CB00231K URL
[11]	Wang YJ, Xue P, Cao MF, et al. Directed evolution: methodologies and applications[J]. Chem Rev, 2021, 121(20): 12384-12444. doi: 10.1021/acs.chemrev.1c00260 pmid: 34297541
[12]	Zhu HL, Zhang HQ, Xu Y, et al. PCR past, present and future[J]. BioTechniques, 2020, 69(4): 317-325. doi: 10.2144/btn-2020-0057 URL
[13]	Chua JPS, Go MK, Osothprarop T, et al. Evolving a thermostable terminal deoxynucleotidyl transferase[J]. ACS Synth Biol, 2020, 9(7): 1725-1735. doi: 10.1021/acssynbio.0c00078 pmid: 32497424
[14]	Hulett HR, Bonner WA, Barrett J, et al. Cell sorting: automated separation of mammalian cells as a function of intracellular fluorescence[J]. Science, 1969, 166(3906): 747-749. pmid: 4898615
[15]	Parks DR, Hardy RR, Herzenberg LA. Three-color immunofluorescence analysis of mouse B-lymphocyte subpopulations[J]. Cytometry, 1984, 5(2): 159-168. pmid: 6370630
[16]	Schweingruber C, Nijssen J, Benitez JA, et al. Single-cell mRNA-seq of in vitro-derived human neurons using smart-Seq2[M]//Transcription Factor Regulatory Networks. New York, NY: Springer US, 2022: 143-164.
[17]	McKinnon KM. Flow cytometry: an overview[J]. Curr Protoc Immunol, 2018, 120: 5.1.1-5.1.11.
[18]	Bonilla DL, Reinin G, Chua E. Full spectrum flow cytometry as a powerful technology for cancer immunotherapy research[J]. Front Mol Biosci, 2021, 7: 612801. doi: 10.3389/fmolb.2020.612801 URL
[19]	Krasteva D, Ivanov Y, Chengolova Z, et al. Simultaneous enumeration of CD34⁺ and CD45⁺ cells using EasyCounter image cytometer[J]. Anal Biochem, 2021, 632: 114351. doi: 10.1016/j.ab.2021.114351 URL
[20]	Wang JH, Tu CG, Zhang H, et al. Loading of metal isotope-containing intercalators for mass cytometry-based high-throughput quantitation of exosome uptake at the single-cell level[J]. Biomaterials, 2020, 255: 120152. doi: 10.1016/j.biomaterials.2020.120152 URL
[21]	Li LJ, Yu SJ, Liu SS, et al. The expression and clinical significance of CD59 and FLAER in Chinese adult AML patients[J]. J Clin Lab Anal, 2022, 36(1): e24145. doi: 10.1002/jcla.v36.1 URL
[22]	Lin DF, Shen LS, Luo M, et al. Circulating tumor cells: biology and clinical significance[J]. Signal Transduct Target Ther, 2021, 6(1): 404.
[23]	Freen-van Heeren JJ. Flow-FISH as a tool for studying bacteria, fungi and viruses[J]. BioTech(Basel), 2021, 10(4): 21.
[24]	Cheng JL, Mao X, Chen CX, et al. Monitoring anti-CD19 chimeric antigen receptor T cell population by flow cytometry and its consistency with digital droplet polymerase chain reaction[J]. Cytometry A, 2023, 103(1): 16-26. doi: 10.1002/cyto.a.v103.1 URL
[25]	Xiao J, Qiu M, Long MZ, et al. Long non-coding RNA XIST impedes LPS-induced AC16 cell inflammation and apoptosis through down-regulating miR-370-3p and regulating PI3K/AKT/mTOR pathways[J]. Comb Chem High Throughput Screen, 2023. DOI.org/10.2174/1386207326666230213124031.
[26]	陈林, 宋丽. 流式细胞术的发展及在植物研究中的应用[J]. 生物工程学报, 2023, 39(2): 472-487.
	Chen L, Song L. Development of flow cytometry and its application in plant research[J]. Chin J Biotechnol, 2023, 39(2): 472-487.
[27]	Shrirao AB, Fritz Z, Novik EM, et al. Microfluidic flow cytometry: the role of microfabrication methodologies, performance and functional specification[J]. Technology, 2018, 6(1): 1-23. doi: 10.1142/S2339547818300019 pmid: 29682599
[28]	Li ZJ, Li PY, Xu J, et al. Hydrodynamic flow cytometer performance enhancement by two-dimensional acoustic focusing[J]. Biomed Microdevices, 2020, 22(2): 27. doi: 10.1007/s10544-020-00481-9 pmid: 32222836
[29]	Robinson JP. Flow cytometry: past and future[J]. BioTechniques, 2022, 72(4): 159-169. doi: 10.2144/btn-2022-0005 pmid: 35369735
[30]	Manohar SM, Shah P, Nair A. Flow cytometry: principles, applications and recent advances[J]. Bioanalysis, 2021, 13(3): 181-198. doi: 10.4155/bio-2020-0267 pmid: 33543666
[31]	Maby P, Corneau A, Galon J. Phenotyping of tumor infiltrating immune cells using mass-cytometry(CyTOF)[J]. Methods Enzymol, 2020, 632: 339-368.
[32]	Robinson JP. Spectral flow cytometry—Quo vadimus?[J]. Cytometry, 2019: cyto.a.23779.
[33]	Liu HS, Tian Y, Xue CF, et al. Analysis of extracellular vesicle DNA at the single-vesicle level by nano-flow cytometry[J]. J Extracell Vesicles, 2022, 11(4): e12206. doi: 10.1002/jev2.v11.4 URL
[34]	Chaganti LK, Venkatakrishnan N, Bose K. An efficient method for FITC labelling of proteins using tandem affinity purification[J]. Biosci Rep, 2018, 38(6): BSR20181764. doi: 10.1042/BSR20181764 URL
[35]	Li JC, Pu KY. Development of organic semiconducting materials for deep-tissue optical imaging, phototherapy and photoactivation[J]. Chem Soc Rev, 2019, 48(1): 38-71. doi: 10.1039/c8cs00001h pmid: 30387803
[36]	Molaei MJ. A review on nanostructured carbon quantum dots and their applications in biotechnology, sensors, and chemiluminescence[J]. Talanta, 2019, 196: 456-478. doi: S0039-9140(18)31309-2 pmid: 30683392
[37]	Saini DK, Pabbi S, Shukla P. Cyanobacterial pigments: perspectives and biotechnological approaches[J]. Food Chem Toxicol, 2018, 120: 616-624. doi: S0278-6915(18)30509-X pmid: 30077705
[38]	Wang MJ, Da YF, Tian Y. Fluorescent proteins and genetically encoded biosensors[J]. Chem Soc Rev, 2023, 52(4): 1189-1214. doi: 10.1039/d2cs00419d pmid: 36722390
[39]	Eilenberger C, Spitz S, Bachmann BEM, et al. The usual suspects 2019: of chips, droplets, synthesis, and artificial cells[J]. Micromachines, 2019, 10(5): 285. doi: 10.3390/mi10050285 URL
[40]	Arbige MV, Shetty JK, Chotani GK. Industrial enzymology: the next chapter[J]. Trends Biotechnol, 2019, 37(12): 1355-1366. doi: S0167-7799(19)30242-2 pmid: 31679826
[41]	Sheldon RA, Woodley JM. Role of biocatalysis in sustainable chemistry[J]. Chem Rev, 2018, 118(2): 801-838. doi: 10.1021/acs.chemrev.7b00203 pmid: 28876904
[42]	Victorino da Silva Amatto I, Gonsales da Rosa-Garzon N, Antônio de Oliveira Simões F, et al. Enzyme engineering and its industrial applications[J]. Biotechnol Appl Biochem, 2022, 69(2): 389-409. doi: 10.1002/bab.v69.2 URL
[43]	Matuła K, Rivello F, Huck WTS. Single-cell analysis using droplet microfluidics[J]. Adv Biosyst, 2020, 4(1): e1900188.
[44]	Weiβ MS, Bornscheuer UT, Höhne M. Solid-phase agar plate assay for screening amine transaminases[J]. Methods Mol Biol, 2018, 1685: 283-296. doi: 10.1007/978-1-4939-7366-8_17 pmid: 29086316
[45]	Karnaouri A, Zerva A, Christakopoulos P, et al. Screening of recombinant lignocellulolytic enzymes through rapid plate assays[J]. Methods Mol Biol, 2021, 2178: 479-503. doi: 10.1007/978-1-0716-0775-6_30 pmid: 33128767
[46]	Jankowski N, Koschorreck K. Agar plate assay for rapid screening of aryl-alcohol oxidase mutant libraries in Pichia pastoris[J]. J Biotechnol, 2022, 346: 47-51. doi: 10.1016/j.jbiotec.2022.01.006 pmid: 35122934
[47]	Diep P, Mahadevan R, Yakunin AF. A microplate screen to estimate metal-binding affinities of metalloproteins[J]. Anal Biochem, 2020, 609: 113836. doi: 10.1016/j.ab.2020.113836 URL
[48]	Koh DWS, Tay JH, Gan SKE. Engineering Ag43 signal peptides with bacterial display and selection[J]. Methods Protoc, 2022, 6(1): 1. doi: 10.3390/mps6010001 URL
[49]	Ma FQ, Chung MT, Yao Y, et al. Efficient molecular evolution to generate enantioselective enzymes using a dual-channel microfluidic droplet screening platform[J]. Nat Commun, 2018, 9(1): 1030. doi: 10.1038/s41467-018-03492-6 pmid: 29531246
[50]	Jiang JJ, Yang GY, Ma FQ. Fluorescence coupling strategies in fluorescence-activated droplet sorting(FADS)for ultrahigh-throughput screening of enzymes, metabolites, and antibodies[J]. Biotechnol Adv, 2023, 66: 108173. doi: 10.1016/j.biotechadv.2023.108173 URL
[51]	Liu YF, Yuan HL, Ding DQ, et al. Establishment of a biosensor-based high-throughput screening platform for tryptophan overproduction[J]. ACS Synth Biol, 2021, 10(6): 1373-1383. doi: 10.1021/acssynbio.0c00647 pmid: 34081459
[52]	Lim J, Petersen M, Bunz M, et al. Flow cytometry based-FRET: basics, novel developments and future perspectives[J]. Cell Mol Life Sci, 2022, 79(4): 217. doi: 10.1007/s00018-022-04232-2 pmid: 35352201
[53]	Keerthana S, Sam B, George L, et al. Fluorescein based fluorescence sensors for the selective sensing of various analytes[J]. J Fluoresc, 2021, 31(5): 1251-1276. doi: 10.1007/s10895-021-02770-9 pmid: 34255257
[54]	Olsen MJ, Stephens D, Griffiths D, et al. Function-based isolation of novel enzymes from a large library[J]. Nat Biotechnol, 2000, 18(10): 1071-1074. pmid: 11017045
[55]	Chen I, Dorr BM, Liu DR. A general strategy for the evolution of bond-forming enzymes using yeast display[J]. Proc Natl Acad Sci USA, 2011, 108(28): 11399-11404. doi: 10.1073/pnas.1101046108 pmid: 21697512
[56]	Feng LL, Gao L, Besirlioglu V, et al. A flow cytometry-based ultrahigh-throughput screening method for directed evolution of oxidases[J]. Angew Chem Int Ed Engl, 2023, 62(22): e202214999. doi: 10.1002/anie.v62.22 URL
[57]	Yang GY, Rich JR, Gilbert M, et al. Fluorescence activated cell sorting as a general ultra-high-throughput screening method for directed evolution of glycosyltransferases[J]. J Am Chem Soc, 2010, 132(30): 10570-10577. doi: 10.1021/ja104167y pmid: 20662530
[58]	Tan YM, Zhang Y, Han YB, et al. Directed evolution of an α1, 3-fucosyltransferase using a single-cell ultrahigh-throughput screening method[J]. Sci Adv, 2019, 5(10): eaaw8451. doi: 10.1126/sciadv.aaw8451 URL
[59]	Shin J, Kim S, Park W, et al. Directed evolution of soluble α-1, 2-fucosyltransferase using kanamycin resistance protein as a phenotypic reporter for efficient production of 2'-fucosyllactose[J]. J Microbiol Biotechnol, 2022, 32(11): 1471-1478. doi: 10.4014/jmb.2209.09018 URL
[60]	Janesch B, Baumann L, Mark A, et al. Directed evolution of bacterial polysialyltransferases[J]. Glycobiology, 2019, 29(7): 588-598. doi: 10.1093/glycob/cwz021 pmid: 30976781
[61]	Kovačević G, Ostafe R, Balaž AM, et al. Development of GFP-based high-throughput screening system for directed evolution of glucose oxidase[J]. J Biosci Bioeng, 2019, 127(1): 30-37. doi: S1389-1723(18)30312-8 pmid: 30033354
[62]	Della Corte D, van Beek HL, Syberg F, et al. Engineering and application of a biosensor with focused ligand specificity[J]. Nat Commun, 2020, 11(1): 4851. doi: 10.1038/s41467-020-18400-0 pmid: 32978386
[63]	Gao JS, Du MH, Zhao JH, et al. Design of a genetically encoded biosensor to establish a high-throughput screening platform for L-cysteine overproduction[J]. Metab Eng, 2022, 73: 144-157. doi: 10.1016/j.ymben.2022.07.007 pmid: 35921946
[64]	Meister SW, Hendrikse NM, Löfblom J. Directed evolution of the 3C protease from coxsackievirus using a novel fluorescence-assisted intracellular method[J]. Biol Chem, 2019, 400(3): 405-415. doi: 10.1515/hsz-2018-0362 pmid: 30521472
[65]	Michener JK, Smolke CD. High-throughput enzyme evolution in Saccharomyces cerevisiae using a synthetic RNA switch[J]. Metab Eng, 2012, 14(4): 306-316. doi: 10.1016/j.ymben.2012.04.004 pmid: 22554528
[66]	Kortmann M, Mack C, Baumgart M, et al. Pyruvate carboxylase variants enabling improved lysine production from glucose identified by biosensor-based high-throughput fluorescence-activated cell sorting screening[J]. ACS Synth Biol, 2019, 8(2): 274-281. doi: 10.1021/acssynbio.8b00510 pmid: 30707564
[67]	Liu C, Zhang B, Liu YM, et al. New intracellular shikimic acid biosensor for monitoring shikimate synthesis in Corynebacterium glutamicum[J]. ACS Synth Biol, 2018, 7(2): 591-601. doi: 10.1021/acssynbio.7b00339 URL
[68]	Zhang X, Zhang XM, Xu GQ, et al. Integration of ARTP mutagenesis with biosensor-mediated high-throughput screening to improve L-serine yield in Corynebacterium glutamicum[J]. Appl Microbiol Biotechnol, 2018, 102(14): 5939-5951. doi: 10.1007/s00253-018-9025-2 pmid: 29725721
[69]	Yang GY, Withers SG. Ultrahigh-throughput FACS-based screening for directed enzyme evolution[J]. Chembiochem, 2009, 10(17): 2704-2715. doi: 10.1002/cbic.200900384 pmid: 19780076
[70]	Zhou GJ, Zhang FZ. Applications and tuning strategies for transcription factor-based metabolite biosensors[J]. Biosensors, 2023, 13(4): 428. doi: 10.3390/bios13040428 URL
[71]	Mohamed M G A, Ambhorkar P, Samanipour R, et al. Microfluidics-based fabrication of cell-laden microgels[J]. Biomicrofluidics, 2020, 14(2): 021501. doi: 10.1063/1.5134060 URL
[72]	Brower KK, Khariton M, Suzuki PH, et al. Double emulsion picoreactors for high-throughput single-cell encapsulation and phenotyping via FACS[J]. Anal Chem, 2020, 92(19): 13262-13270. doi: 10.1021/acs.analchem.0c02499 URL
[73]	Schaerli Y. Bacterial microcolonies in gel beads for high-throughput screening[J]. Bio-protocol, 2018, 8(13): e2911.
[74]	Aharoni A, Amitai G, Bernath K, et al. High-throughput screening of enzyme libraries: thiolactonases evolved by fluorescence-activated sorting of single cells in emulsion compartments[J]. Chem Biol, 2005, 12(12): 1281-1289. doi: 10.1016/j.chembiol.2005.09.012 URL
[75]	Zinchenko A, Devenish SRA, Kintses B, et al. One in a million: flow cytometric sorting of single cell-lysate assays in monodisperse picolitre double emulsion droplets for directed evolution[J]. Anal Chem, 2014, 86(5): 2526-2533. doi: 10.1021/ac403585p pmid: 24517505
[76]	Larsen AC, Dunn MR, Hatch A, et al. A general strategy for expanding polymerase function by droplet microfluidics[J]. Nat Commun, 2016, 7: 11235. doi: 10.1038/ncomms11235 pmid: 27044725
[77]	Menghiu G, Ostafe V, Prodanović R, et al. A high-throughput screening system based on fluorescence-activated cell sorting for the directed evolution of chitinase A[J]. Int J Mol Sci, 2021, 22(6): 3041. doi: 10.3390/ijms22063041 URL
[78]	Vallapurackal J, Stucki A, Liang AD, et al. Ultrahigh-throughput screening of an artificial metalloenzyme using double emulsions[J]. Angew Chem Int Ed Engl, 2022, 61(48): e202207328. doi: 10.1002/anie.v61.48 URL
[79]	Eun YJ, Utada AS, Copeland MF, et al. Encapsulating bacteria in agarose microparticles using microfluidics for high-throughput cell analysis and isolation[J]. ACS Chem Biol, 2011, 6(3): 260-266. doi: 10.1021/cb100336p URL
[80]	Pitzler C, Wirtz G, Vojcic L, et al. A fluorescent hydrogel-based flow cytometry high-throughput screening platform for hydrolytic enzymes[J]. Chem Biol, 2014, 21(12): 1733-1742. doi: 10.1016/j.chembiol.2014.10.018 URL
[81]	Ma CX, Tan ZL, Lin Y, et al. Gel microdroplet-based high-throughput screening for directed evolution of xylanase-producing Pichia pastoris[J]. J Biosci Bioeng, 2019, 128(6): 662-668. doi: 10.1016/j.jbiosc.2019.05.008 URL
[82]	Gianella P, Snapp EL, Levy M. An in vitro compartmentalization-based method for the selection of bond-forming enzymes from large libraries[J]. Biotechnol Bioeng, 2016, 113(8): 1647-1657. doi: 10.1002/bit.25939 pmid: 26806853
[83]	Bernath K, Hai MT, Mastrobattista E, et al. In vitro compartmentalization by double emulsions: sorting and gene enrichment by fluorescence activated cell sorting[J]. Anal Biochem, 2004, 325(1): 151-157. pmid: 14715296
[84]	Watanabe T, Motohiro I, Ono T. Microfluidic formation of hydrogel microcapsules with a single aqueous core by spontaneous cross-linking in aqueous two-phase system droplets[J]. Langmuir, 2019, 35(6): 2358-2367. doi: 10.1021/acs.langmuir.8b04169 pmid: 30626189
[85]	Lai EP, Bao BY, Zhu YF, et al. Transglutaminase-catalyzed bottom-up synthesis of polymer hydrogel[J]. Front Bioeng Biotechnol, 2022, 10: 824747. doi: 10.3389/fbioe.2022.824747 URL
[86]	Zhan J, Sun HY, Xie MM, et al. Hyperbranched polyamidoamine-chitosan polyelectrolyte gels crosslinking by polyacrylic acid and alginate for removal of anionic dyes[J]. Int J Biol Macromol, 2022, 222(Pt B): 3024-3033. doi: 10.1016/j.ijbiomac.2022.10.077 URL
[87]	Li M, Liu HR, Zhuang SY, et al. Droplet flow cytometry for single-cell analysis[J]. RSC Adv, 2021, 11(34): 20944-20960. doi: 10.1039/d1ra02636d pmid: 35479393
[88]	Bilal M, Cui JD, Iqbal HMN. Tailoring enzyme microenvironment: state-of-the-art strategy to fulfill the quest for efficient bio-catalysis[J]. Int J Biol Macromol, 2019, 130: 186-196. doi: S0141-8130(18)37157-5 pmid: 30817963
[89]	Markel U, Essani KD, Besirlioglu V, et al. Advances in ultrahigh-throughput screening for directed enzyme evolution[J]. Chem Soc Rev, 2020, 49(1): 233-262. doi: 10.1039/c8cs00981c pmid: 31815263
[90]	Medcalf EJ, Gantz M, Kaminski TS, et al. Ultra-high-throughput absorbance-activated droplet sorting for enzyme screening at kilohertz frequencies[J]. Anal Chem, 2023, 95(10): 4597-4604. doi: 10.1021/acs.analchem.2c04144 URL
[91]	康里奇, 谈攀, 洪亮. 人工智能时代下的酶工程[J]. 合成生物学, 2023. https://kns.cnki.net/kcms/detail/10.1687.q.20230407.1430.002.html.
	Kang LQ, Tan P, Hong L. Enzyme engineering in the age of artificial intelligence[J]. Synthetic Biology Journal, 2023. https://kns.cnki.net/kcms/detail/10.1687.q.20230407.1430.002.html.
[92]	曲玉辰, 陆路, 姜世勃. 利用I-Mutant2.0辅助设计与优化中东呼吸综合征冠状病毒融合抑制多肽[J]. 微生物与感染, 2019, 14(2): 72-81.
	Qu YC, Lu L, Jiang SB. Using I-Mutant2.0 to assist the design and optimization of MERS-CoV fusion inhibitory peptides[J]. J Microbes Infect, 2019, 14(2): 72-81.
[93]	Yang Y, Ding XS, Zhu GC, et al. ProTstab - predictor for cellular protein stability[J]. BMC Genomics, 2019, 20(1): 804. doi: 10.1186/s12864-019-6138-7 pmid: 31684883
[94]	Meier J, Rao R, Verkuil R, et al. Language models enable zero-shot prediction of the effects of mutations on protein function[J]. Advances in Neural Information Processing Systems, 2021, 34: 29287-23303.

筛选方法 Screening method	通量 Throughput	突变文库 Mutant library	特点 Characteristic	参考文献 References
平板		10⁵-10⁶	操作简便；半定量分析；通量低；精度低	[44,45,46,47]
微孔板	1/s	10⁵	操作简便；定量分析；通量低；精度低	[13, 47]
FACS	10⁴/s	>10⁸	通量高；消耗少；精度高；单细胞定量分析；设备昂贵；不便携	[8, 48]
FADS	<10³/s	10⁷	通量高；消耗少；精度高；单细胞定量分析；工艺复杂度高；搭建难	[43, 49-51]

筛选方法 Screening method	通量 Throughput	突变文库 Mutant library	特点 Characteristic	参考文献 References
平板		10⁵-10⁶	操作简便；半定量分析；通量低；精度低	[44,45,46,47]
微孔板	1/s	10⁵	操作简便；定量分析；通量低；精度低	[13, 47]
FACS	10⁴/s	>10⁸	通量高；消耗少；精度高；单细胞定量分析；设备昂贵；不便携	[8, 48]
FADS	<10³/s	10⁷	通量高；消耗少；精度高；单细胞定量分析；工艺复杂度高；搭建难	[43, 49-51]

类别 Classification	目标酶 Target enzyme	结果 Result	宿主细胞 Host cell	参考文献 Reference
细胞表面酶	丝氨酸蛋白酶OmpT	k_cat/K_m值提高60倍	大肠杆菌E. coli	[54]
	分选酶A	k_cat/K_m值提高140倍	酿酒酵母S. cerevisiae	[55]
	半乳糖氧化酶	K_m值降低4.4倍	大肠杆菌E. coli	[56]
	D-氨基酸氧化酶	k_cat值提高4.2倍	大肠杆菌E. coli	[56]
胞内酶	β-1,3-半乳糖基转移酶	底物耐受性提高300倍	大肠杆菌E. coli	[57]
	α-1,3-岩藻糖基转移酶	合成Lewis X和3'岩藻糖基乳糖的k_cat/K_m值分别提高6倍和14倍	幽门螺旋杆菌Helicobacter pylori	[58]
	α-1,2-岩藻糖基转移酶	2'岩藻糖基乳糖的滴度和产量分别提高1.72倍和1.51倍	大肠杆菌E. coli	[59]
	多聚唾液酸转移酶	比酶活和热稳定性分别提高 1.5-2.1倍和9倍	奈瑟菌Neisseria	[60]
	葡萄糖氧化酶	V_max值分别提高1.3和2.3倍	酿酒酵母S. cerevisiae	[61]
	ATP磷酸核糖转移酶	L-组氨酸产量为0.1 mmol/L，野生型未生产L-组氨酸	谷氨酸棒状杆菌Corynebacterium glutamicum	[62]
	丝氨酸乙酰转移酶	L-半胱氨酸产量提高2.36倍	大肠杆菌E. coli	[63]
	3C蛋白酶	蛋白水解活性提高4倍	大肠杆菌E. coli	[64]
	咖啡因去甲基化酶	V_max/K_m值和产物选择性分别提高33和22倍	酿酒酵母S. cerevisiae	[65]
	丙酮酸羧化酶	赖氨酸滴度分别增加9%和19%	谷氨酸棒状杆菌C. glutamicum	[66]
	莽草酸生产菌株	莽草酸滴度达到（3.72±0.35）mmol/L，比野生型提高2.4倍	谷氨酸棒状杆菌C. glutamicum	[67]
	丝氨酸羟甲基转移酶	L-丝氨酸产量达到34.78 g/L，比野生型菌株提高35.9%	谷氨酸棒状杆菌C. glutamicum	[68]

类别 Classification	目标酶 Target enzyme	结果 Result	宿主细胞 Host cell	参考文献 Reference
细胞表面酶	丝氨酸蛋白酶OmpT	k_cat/K_m值提高60倍	大肠杆菌E. coli	[54]
	分选酶A	k_cat/K_m值提高140倍	酿酒酵母S. cerevisiae	[55]
	半乳糖氧化酶	K_m值降低4.4倍	大肠杆菌E. coli	[56]
	D-氨基酸氧化酶	k_cat值提高4.2倍	大肠杆菌E. coli	[56]
胞内酶	β-1,3-半乳糖基转移酶	底物耐受性提高300倍	大肠杆菌E. coli	[57]
	α-1,3-岩藻糖基转移酶	合成Lewis X和3'岩藻糖基乳糖的k_cat/K_m值分别提高6倍和14倍	幽门螺旋杆菌Helicobacter pylori	[58]
	α-1,2-岩藻糖基转移酶	2'岩藻糖基乳糖的滴度和产量分别提高1.72倍和1.51倍	大肠杆菌E. coli	[59]
	多聚唾液酸转移酶	比酶活和热稳定性分别提高 1.5-2.1倍和9倍	奈瑟菌Neisseria	[60]
	葡萄糖氧化酶	V_max值分别提高1.3和2.3倍	酿酒酵母S. cerevisiae	[61]
	ATP磷酸核糖转移酶	L-组氨酸产量为0.1 mmol/L，野生型未生产L-组氨酸	谷氨酸棒状杆菌Corynebacterium glutamicum	[62]
	丝氨酸乙酰转移酶	L-半胱氨酸产量提高2.36倍	大肠杆菌E. coli	[63]
	3C蛋白酶	蛋白水解活性提高4倍	大肠杆菌E. coli	[64]
	咖啡因去甲基化酶	V_max/K_m值和产物选择性分别提高33和22倍	酿酒酵母S. cerevisiae	[65]
	丙酮酸羧化酶	赖氨酸滴度分别增加9%和19%	谷氨酸棒状杆菌C. glutamicum	[66]
	莽草酸生产菌株	莽草酸滴度达到（3.72±0.35）mmol/L，比野生型提高2.4倍	谷氨酸棒状杆菌C. glutamicum	[67]
	丝氨酸羟甲基转移酶	L-丝氨酸产量达到34.78 g/L，比野生型菌株提高35.9%	谷氨酸棒状杆菌C. glutamicum	[68]

类别 Classification	目标酶 Target enzyme	结果 Result	宿主细胞 Host cell	参考文献 Reference
双乳化液滴法	血清对氧磷酶	k_cat/K_m值提高100倍	大肠杆菌E. coli	[74]
	碱性磷酸酶	实现活性碱性磷酸酶的100万倍富集	大肠杆菌E. coli	[75]
	α-L-苏糖核酸聚合酶	获得一个不依赖于锰的α-L-苏氨酸核糖核酸（TNA）聚合酶突变体	大肠杆菌E. coli	[76]
	几丁质酶A	比酶活提高2倍	大肠杆菌E. coli	[77]
	人工金属酶	建立FACS筛选双乳化液滴中人工金属酶的方法	大肠杆菌E. coli	[78]
水凝胶微珠法	RNA聚合酶	获得一个对利福霉素有耐药性的突变体	大肠杆菌E. coli	[79]
	植酸酶	k_cat值提高31%	大肠杆菌E. coli	[80]
	木聚糖酶	比酶活提高1.3倍	毕赤酵母Pichia pastoris	[81]
	转肽酶	k_cat/K_m值提高114倍	大肠杆菌E. coli	[82]